Monitoring and investigating situations
Some of the major benefits of ML-based situations are:
Advanced noise reduction and reduced mean time to resolve (MTTR)
- The AI/ML algorithm uses an event signature to analyze topological and temporal relationships to create situations in the context of the impacted services.
- BMC Helix AIOps uses advanced configuration settings to determine the event aggregation window and groups situations into primary, related, and similar situations.
Direct path to probable or root cause of the impact
- The algorithm analyzes, ranks, and displays the top-most situations.
- A cross-launch link from the situation to the impacted service helps with the root cause analysis.
Generative AI-driven remediation recommendations, actionable insights from logs, and other capabilities by connecting with BMC HelixGPT
- BMC Helix AIOps leverages the generative AI capabilities of BMC HelixGPT to provide a step-by-step remediation plan for a situation. Wherever applicable, a code wizard provides a script that can be used to automate a remediation step.
- The connection with BMC HelixGPT generates actionable insights from logs available in BMC Helix Log Analytics.
Automated problem remediation
BMC Helix AIOps provides the ability to remediate situations manually or automatically by connecting with BMC Helix Intelligent Automation.
The following diagram shows a high-level process for managing situations in BMC Helix AIOps:
Learn about the advanced monitoring and analytical capabilities by using the topics listed in the following table:
Action | Reference |
---|---|
Learn about types of situations, situation groups, best action recommendations, log insights, and incidents for situations. | |
Learn how to monitor independent, primary, and similar situations. | |
Learn how to view and investigate:
| |
Learn how to perform actions on situations or on the events within a situation. |